[AAAI 2022] Sparse Structure Learning via Graph Neural Networks for Inductive Document Classification

Related tags

Deep Learning document-classification sparse-reconstruction aaai2022
Overview

Sparse Structure Learning via Graph Neural Networks for inductive document classification

Make graph dataset

  1. create co-occurrence graph for datasets.

    python ssl_make_graphs/create_cooc_document.py --raw_path SOURCEPATH --pre_path TARGETPATH --task DATASET --partition TRAINorTEST --window_size SIZE

  2. construct in memory graph datsets.

    python ssl_make_graphs/PygDocsGraphDatset.py --raw_path SOURCEPATH --task DATASET

Reproduce

python ssl_graphmodels/pyg_models/train_docs.py
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Comments
  • TypeError: __inc__() takes 3 positional arguments but 4 were given

    TypeError: __inc__() takes 3 positional arguments but 4 were given

    When run python ssl_graphmodels/pyg_models/train_docs.py --name R8

    building gnn_note_attn_gumbel model... train and validate: 0/200 | | Traceback (most recent call last): File "D:\Code\TextSSL\ssl_graphmodels\pyg_models\train_docs.py", line 126, in best_model, best_epoch, test_results, all_results, best_preds, labels = train_main(train_loader, val_loader, test_loader, params['patience']) File "D:\Code\TextSSL\ssl_graphmodels\pyg_models\train_docs.py", line 70, in train_main train_loss = train(train_loader, training=True) File "D:\Code\TextSSL\ssl_graphmodels\pyg_models\train_docs.py", line 22, in train for index, data in enumerate(loader): File "D:\Anaconda\envs\pytorch\lib\site-packages\torch\utils\data\dataloader.py", line 521, in next data = self._next_data() File "D:\Anaconda\envs\pytorch\lib\site-packages\torch\utils\data\dataloader.py", line 561, in _next_data data = self._dataset_fetcher.fetch(index) # may raise StopIteration File "D:\Anaconda\envs\pytorch\lib\site-packages\torch\utils\data_utils\fetch.py", line 52, in fetch return self.collate_fn(data) File "D:\Anaconda\envs\pytorch\lib\site-packages\torch_geometric\loader\dataloader.py", line 19, in call return Batch.from_data_list(batch, self.follow_batch, File "D:\Anaconda\envs\pytorch\lib\site-packages\torch_geometric\data\batch.py", line 68, in from_data_list batch, slice_dict, inc_dict = collate( File "D:\Anaconda\envs\pytorch\lib\site-packages\torch_geometric\data\collate.py", line 84, in collate value, slices, incs = _collate(attr, values, data_list, stores, File "D:\Anaconda\envs\pytorch\lib\site-packages\torch_geometric\data\collate.py", line 133, in _collate incs = get_incs(key, values, data_list, stores) File "D:\Anaconda\envs\pytorch\lib\site-packages\torch_geometric\data\collate.py", line 223, in get_incs repeats = [ File "D:\Anaconda\envs\pytorch\lib\site-packages\torch_geometric\data\collate.py", line 224, in data.inc(key, value, store) TypeError: inc() takes 3 positional arguments but 4 were given

    My env shows below: PyG:2.0.4 Pytorch:1.10 CUDA:11.3 OS:Win10

    opened by EldenRingChen 1
  • RuntimeError: start (0) + length (278) exceeds dimension size (2).

    RuntimeError: start (0) + length (278) exceeds dimension size (2).

    Could you tell me which version of pyg you use? when i run train_docs.py, there is an error:

    .........., line 65, in _separate value = value.narrow(cat_dim or 0, start, end - start)

    "RuntimeError: start (0) + length (278) exceeds dimension size (2)."

    opened by shawn-dm 1
Owner
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GitHub
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